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{bio,medical} informatics


Saturday, March 03, 2001

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find related articles. powered by google. The Scientist Targeting HIV Therapy with Intelligence
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"With an arsenal of 17 approved drugs and intricate rules for deploying each one, a physician's battle to shut down HIV replication is like chess against an opponent too strong to be driven from the board, so keeping the game going is the only alternative to losing. Today's best strategy for suppressing HIV calls for using three or four inhibitors in combination. As with a chessboard siege defense, conserving pieces while sealing off each new attack, doctors try to pick drug combinations that preserve as many options as possible should HIV mutate into drug resistance.

To help doctors find the most promising combinations in any situation, software called the HIV Therapy Edge combines bioinformatics with artificial intelligence, a computer science discipline grown up on chess problems. Developed by Intelligent Thera-peutic Solutions of Durham, N.C., the product is in final testing, scheduled for market release sometime this summer. HIV Therapy Edge, says John Mellors of the University of Pittsburgh, "does in milliseconds what would take me 20 or 30 minutes sitting down in a quiet room, leafing through a patient's charts, checking the past medical history, virus resistance profiles, drug doses and interactions, pulling together all my knowledge.""
redux [07.06.00]
find related articles. powered by google. HMS Beagle Latent resistance
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"New treatments have extended the lives of AIDS patients and offered hope for a cure, but multidrug-resistant strains can still foil therapy. Researchers used analysis and computer simulations to show that resistance-related treatment failure in patients who consistently take their prescribed drugs is likely due to mutant strains present at the beginning of treatment rather than strains developing during the course of treatment as a result of residual viral replication. The finding stresses the importance of combining drugs with different resistance profiles in order to wipe out all existing drug-resistant strains of the virus early in treatment."

Reference: Ribeiro, R.M. and Bonhoeffer, S. 2000. Production of resistant HIV mutants during antiretroviral therapy. Proc. Natl. Acad. Sci. U.S.A. 97(14):7681-7686."
find related articles. powered by google. Proceedings of the National Academy of Sciences Production of resistant HIV mutants during antiretroviral therapy
"HIV drug therapy often fails because of the appearance of multidrug-resistant virus. There are two possible scenarios for the outgrowth of multidrug-resistant virus in response to therapy. Resistant virus may preexist at low frequencies in drug-naïve patients and is rapidly selected in the presence of drugs. Alternatively, resistant virus is absent at the start of therapy but is generated by residual viral replication during therapy. Currently available experimental methods are generally too insensitive to distinguish between these two scenarios. Here we use deterministic and stochastic models to investigate the origin of multidrug resistance. We quantify the probabilities that resistant mutants preexist, and that resistant mutants are generated during therapy. The models suggest that under a wide range of conditions, treatment failure is most likely caused by the preexistence of resistant mutants."
redux [04.05.00]
find related articles. powered by google. HMS Beagle Are Computers Evolving in Biology?
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"I suspect that although the new enthusiasm for computers in biology is genuine, it overlooks some basic problems in implementation. The basic difficulty, as I see it, is that although biologists use computers, they do not trust everything that comes out of them. It is one thing to use them to print up nice-looking graphs, but it is an entirely different matter to use them to think better."

"Francis Crick was once quoted as saying that no biologist had ever made a discovery using a mathematical model. I would reply that no biologist has ever made a discovery by running an electrophoretic gel. They make discoveries by using their brains. Computers, like all scientific tools, are only as good as the person who uses them. If biologists don't understand how computer models are constructed, they won't know their strengths and limitations. Without some foundation of trust, biologists will be unlikely to utilize or accept this powerful method of data analysis."


[ rhetoric ]

Bioinformatics will be at the core of biology in the 21st century. In fields ranging from structural biology to genomics to biomedical imaging, ready access to data and analytical tools are fundamentally changing the way investigators in the life sciences conduct research and approach problems. Complex, computationally intensive biological problems are now being addressed and promise to significantly advance our understanding of biology and medicine. No biological discipline will be unaffected by these technological breakthroughs.

BIOINFORMATICS IN THE 21st CENTURY

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